Overview

Dataset statistics

Number of variables18
Number of observations12330
Missing cells0
Missing cells (%)0.0%
Duplicate rows76
Duplicate rows (%)0.6%
Total size in memory1.2 MiB
Average record size in memory102.0 B

Variable types

Numeric14
Categorical2
Boolean2

Alerts

Dataset has 76 (0.6%) duplicate rowsDuplicates
Administrative is highly overall correlated with Administrative_DurationHigh correlation
Administrative_Duration is highly overall correlated with AdministrativeHigh correlation
BounceRates is highly overall correlated with ExitRatesHigh correlation
ExitRates is highly overall correlated with BounceRates and 1 other fieldsHigh correlation
Informational is highly overall correlated with Informational_DurationHigh correlation
Informational_Duration is highly overall correlated with InformationalHigh correlation
ProductRelated is highly overall correlated with ExitRates and 1 other fieldsHigh correlation
ProductRelated_Duration is highly overall correlated with ProductRelatedHigh correlation
VisitorType is highly imbalanced (59.9%)Imbalance
Administrative has 5768 (46.8%) zerosZeros
Administrative_Duration has 5903 (47.9%) zerosZeros
Informational has 9699 (78.7%) zerosZeros
Informational_Duration has 9925 (80.5%) zerosZeros
ProductRelated_Duration has 755 (6.1%) zerosZeros
BounceRates has 5518 (44.8%) zerosZeros
PageValues has 9600 (77.9%) zerosZeros
SpecialDay has 11079 (89.9%) zerosZeros

Reproduction

Analysis started2025-12-10 16:38:07.481365
Analysis finished2025-12-10 16:38:27.864643
Duration20.38 seconds
Software versionydata-profiling vv4.18.0
Download configurationconfig.json

Variables

Administrative
Real number (ℝ)

High correlation  Zeros 

Distinct27
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3151663
Minimum0
Maximum27
Zeros5768
Zeros (%)46.8%
Negative0
Negative (%)0.0%
Memory size48.3 KiB
2025-12-10T17:38:27.998613image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile9
Maximum27
Range27
Interquartile range (IQR)4

Descriptive statistics

Standard deviation3.3217841
Coefficient of variation (CV)1.4347929
Kurtosis4.7011462
Mean2.3151663
Median Absolute Deviation (MAD)1
Skewness1.9603572
Sum28546
Variance11.03425
MonotonicityNot monotonic
2025-12-10T17:38:28.175148image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
05768
46.8%
11354
 
11.0%
21114
 
9.0%
3915
 
7.4%
4765
 
6.2%
5575
 
4.7%
6432
 
3.5%
7338
 
2.7%
8287
 
2.3%
9225
 
1.8%
Other values (17)557
 
4.5%
ValueCountFrequency (%)
05768
46.8%
11354
 
11.0%
21114
 
9.0%
3915
 
7.4%
4765
 
6.2%
5575
 
4.7%
6432
 
3.5%
7338
 
2.7%
8287
 
2.3%
9225
 
1.8%
ValueCountFrequency (%)
271
 
< 0.1%
261
 
< 0.1%
244
 
< 0.1%
233
 
< 0.1%
224
 
< 0.1%
212
 
< 0.1%
202
 
< 0.1%
196
 
< 0.1%
1812
0.1%
1716
0.1%

Administrative_Duration
Real number (ℝ)

High correlation  Zeros 

Distinct3335
Distinct (%)27.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80.818611
Minimum0
Maximum3398.75
Zeros5903
Zeros (%)47.9%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2025-12-10T17:38:28.299866image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median7.5
Q393.25625
95-th percentile348.26637
Maximum3398.75
Range3398.75
Interquartile range (IQR)93.25625

Descriptive statistics

Standard deviation176.77911
Coefficient of variation (CV)2.1873564
Kurtosis50.556739
Mean80.818611
Median Absolute Deviation (MAD)7.5
Skewness5.615719
Sum996493.47
Variance31250.853
MonotonicityNot monotonic
2025-12-10T17:38:28.425149image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
05903
47.9%
456
 
0.5%
553
 
0.4%
745
 
0.4%
1142
 
0.3%
641
 
0.3%
1437
 
0.3%
935
 
0.3%
1533
 
0.3%
1032
 
0.3%
Other values (3325)6053
49.1%
ValueCountFrequency (%)
05903
47.9%
1.3333333331
 
< 0.1%
215
 
0.1%
326
 
0.2%
3.54
 
< 0.1%
456
 
0.5%
4.3333333331
 
< 0.1%
4.52
 
< 0.1%
4.751
 
< 0.1%
553
 
0.4%
ValueCountFrequency (%)
3398.751
< 0.1%
2720.51
< 0.1%
2657.3180561
< 0.1%
2629.2539681
< 0.1%
2407.423811
< 0.1%
2156.1666671
< 0.1%
2137.1127451
< 0.1%
2086.751
< 0.1%
2047.2348481
< 0.1%
1951.2791411
< 0.1%

Informational
Real number (ℝ)

High correlation  Zeros 

Distinct17
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.50356853
Minimum0
Maximum24
Zeros9699
Zeros (%)78.7%
Negative0
Negative (%)0.0%
Memory size48.3 KiB
2025-12-10T17:38:28.523316image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3
Maximum24
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.2701564
Coefficient of variation (CV)2.522311
Kurtosis26.932266
Mean0.50356853
Median Absolute Deviation (MAD)0
Skewness4.0364638
Sum6209
Variance1.6132973
MonotonicityNot monotonic
2025-12-10T17:38:28.612975image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
09699
78.7%
11041
 
8.4%
2728
 
5.9%
3380
 
3.1%
4222
 
1.8%
599
 
0.8%
678
 
0.6%
736
 
0.3%
915
 
0.1%
814
 
0.1%
Other values (7)18
 
0.1%
ValueCountFrequency (%)
09699
78.7%
11041
 
8.4%
2728
 
5.9%
3380
 
3.1%
4222
 
1.8%
599
 
0.8%
678
 
0.6%
736
 
0.3%
814
 
0.1%
915
 
0.1%
ValueCountFrequency (%)
241
 
< 0.1%
161
 
< 0.1%
142
 
< 0.1%
131
 
< 0.1%
125
 
< 0.1%
111
 
< 0.1%
107
 
0.1%
915
0.1%
814
 
0.1%
736
0.3%

Informational_Duration
Real number (ℝ)

High correlation  Zeros 

Distinct1258
Distinct (%)10.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34.472398
Minimum0
Maximum2549.375
Zeros9925
Zeros (%)80.5%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2025-12-10T17:38:28.712691image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile195
Maximum2549.375
Range2549.375
Interquartile range (IQR)0

Descriptive statistics

Standard deviation140.74929
Coefficient of variation (CV)4.0829563
Kurtosis76.316853
Mean34.472398
Median Absolute Deviation (MAD)0
Skewness7.5791847
Sum425044.67
Variance19810.364
MonotonicityNot monotonic
2025-12-10T17:38:28.831546image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
09925
80.5%
933
 
0.3%
626
 
0.2%
1026
 
0.2%
726
 
0.2%
1323
 
0.2%
1223
 
0.2%
1622
 
0.2%
822
 
0.2%
1121
 
0.2%
Other values (1248)2183
 
17.7%
ValueCountFrequency (%)
09925
80.5%
13
 
< 0.1%
1.51
 
< 0.1%
211
 
0.1%
2.51
 
< 0.1%
316
 
0.1%
3.51
 
< 0.1%
417
 
0.1%
518
 
0.1%
5.53
 
< 0.1%
ValueCountFrequency (%)
2549.3751
< 0.1%
2256.9166671
< 0.1%
2252.0333331
< 0.1%
2195.31
< 0.1%
2166.51
< 0.1%
2050.4333331
< 0.1%
1949.1666671
< 0.1%
1830.51
< 0.1%
1779.1666671
< 0.1%
17781
< 0.1%

ProductRelated
Real number (ℝ)

High correlation 

Distinct311
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.731468
Minimum0
Maximum705
Zeros38
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size48.3 KiB
2025-12-10T17:38:28.941044image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median18
Q338
95-th percentile109
Maximum705
Range705
Interquartile range (IQR)31

Descriptive statistics

Standard deviation44.475503
Coefficient of variation (CV)1.4016214
Kurtosis31.211707
Mean31.731468
Median Absolute Deviation (MAD)13
Skewness4.3415164
Sum391249
Variance1978.0704
MonotonicityNot monotonic
2025-12-10T17:38:29.067303image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1622
 
5.0%
2465
 
3.8%
3458
 
3.7%
4404
 
3.3%
6396
 
3.2%
7391
 
3.2%
5382
 
3.1%
8370
 
3.0%
10330
 
2.7%
9317
 
2.6%
Other values (301)8195
66.5%
ValueCountFrequency (%)
038
 
0.3%
1622
5.0%
2465
3.8%
3458
3.7%
4404
3.3%
5382
3.1%
6396
3.2%
7391
3.2%
8370
3.0%
9317
2.6%
ValueCountFrequency (%)
7051
< 0.1%
6861
< 0.1%
5841
< 0.1%
5341
< 0.1%
5181
< 0.1%
5171
< 0.1%
5011
< 0.1%
4861
< 0.1%
4701
< 0.1%
4491
< 0.1%

ProductRelated_Duration
Real number (ℝ)

High correlation  Zeros 

Distinct9551
Distinct (%)77.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1194.7462
Minimum0
Maximum63973.522
Zeros755
Zeros (%)6.1%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2025-12-10T17:38:29.183110image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1184.1375
median598.9369
Q31464.1572
95-th percentile4300.2891
Maximum63973.522
Range63973.522
Interquartile range (IQR)1280.0197

Descriptive statistics

Standard deviation1913.6693
Coefficient of variation (CV)1.6017371
Kurtosis137.17416
Mean1194.7462
Median Absolute Deviation (MAD)500.9369
Skewness7.2632277
Sum14731221
Variance3662130.1
MonotonicityNot monotonic
2025-12-10T17:38:29.297844image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0755
 
6.1%
1721
 
0.2%
817
 
0.1%
1117
 
0.1%
1516
 
0.1%
2215
 
0.1%
1215
 
0.1%
1915
 
0.1%
714
 
0.1%
1314
 
0.1%
Other values (9541)11431
92.7%
ValueCountFrequency (%)
0755
6.1%
0.51
 
< 0.1%
12
 
< 0.1%
2.3333333331
 
< 0.1%
2.6666666671
 
< 0.1%
35
 
< 0.1%
410
 
0.1%
513
 
0.1%
5.3333333331
 
< 0.1%
65
 
< 0.1%
ValueCountFrequency (%)
63973.522231
< 0.1%
43171.233381
< 0.1%
29970.465971
< 0.1%
27009.859431
< 0.1%
24844.15621
< 0.1%
23888.811
< 0.1%
23342.082051
< 0.1%
23050.104141
< 0.1%
21857.046481
< 0.1%
21672.244251
< 0.1%

BounceRates
Real number (ℝ)

High correlation  Zeros 

Distinct1872
Distinct (%)15.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.02219138
Minimum0
Maximum0.2
Zeros5518
Zeros (%)44.8%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2025-12-10T17:38:29.411147image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0.0031124675
Q30.016812558
95-th percentile0.2
Maximum0.2
Range0.2
Interquartile range (IQR)0.016812558

Descriptive statistics

Standard deviation0.048488322
Coefficient of variation (CV)2.185007
Kurtosis7.7231594
Mean0.02219138
Median Absolute Deviation (MAD)0.0031124675
Skewness2.9478553
Sum273.61972
Variance0.0023511174
MonotonicityNot monotonic
2025-12-10T17:38:29.529636image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
05518
44.8%
0.2700
 
5.7%
0.066666667134
 
1.1%
0.028571429115
 
0.9%
0.05113
 
0.9%
0.033333333101
 
0.8%
0.025100
 
0.8%
0.01666666799
 
0.8%
0.198
 
0.8%
0.0496
 
0.8%
Other values (1862)5256
42.6%
ValueCountFrequency (%)
05518
44.8%
2.73 × 10-51
 
< 0.1%
3.35 × 10-51
 
< 0.1%
3.83 × 10-51
 
< 0.1%
3.94 × 10-51
 
< 0.1%
7.09 × 10-51
 
< 0.1%
7.27 × 10-51
 
< 0.1%
7.5 × 10-51
 
< 0.1%
8.01 × 10-51
 
< 0.1%
8.08 × 10-51
 
< 0.1%
ValueCountFrequency (%)
0.2700
5.7%
0.1833333331
 
< 0.1%
0.185
 
< 0.1%
0.1769230771
 
< 0.1%
0.1751
 
< 0.1%
0.1666666674
 
< 0.1%
0.1642857141
 
< 0.1%
0.1642307691
 
< 0.1%
0.1619047621
 
< 0.1%
0.163
 
< 0.1%

ExitRates
Real number (ℝ)

High correlation 

Distinct4777
Distinct (%)38.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.043072798
Minimum0
Maximum0.2
Zeros76
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2025-12-10T17:38:29.658360image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.004567568
Q10.014285714
median0.025156403
Q30.05
95-th percentile0.2
Maximum0.2
Range0.2
Interquartile range (IQR)0.035714286

Descriptive statistics

Standard deviation0.048596541
Coefficient of variation (CV)1.128242
Kurtosis4.0170346
Mean0.043072798
Median Absolute Deviation (MAD)0.01417258
Skewness2.148789
Sum531.0876
Variance0.0023616238
MonotonicityNot monotonic
2025-12-10T17:38:29.778069image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.2710
 
5.8%
0.1338
 
2.7%
0.05329
 
2.7%
0.033333333291
 
2.4%
0.066666667267
 
2.2%
0.025224
 
1.8%
0.04214
 
1.7%
0.016666667181
 
1.5%
0.02167
 
1.4%
0.022222222152
 
1.2%
Other values (4767)9457
76.7%
ValueCountFrequency (%)
076
0.6%
0.0001755931
 
< 0.1%
0.0002504381
 
< 0.1%
0.0002621231
 
< 0.1%
0.0002631581
 
< 0.1%
0.0002923981
 
< 0.1%
0.0004098361
 
< 0.1%
0.0004464291
 
< 0.1%
0.0004683841
 
< 0.1%
0.0004807691
 
< 0.1%
ValueCountFrequency (%)
0.2710
5.8%
0.1923076921
 
< 0.1%
0.1888888892
 
< 0.1%
0.1866666674
 
< 0.1%
0.1833333332
 
< 0.1%
0.1818181821
 
< 0.1%
0.180341881
 
< 0.1%
0.183
 
< 0.1%
0.1777777785
 
< 0.1%
0.1756
 
< 0.1%

PageValues
Real number (ℝ)

Zeros 

Distinct2704
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.8892579
Minimum0
Maximum361.76374
Zeros9600
Zeros (%)77.9%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2025-12-10T17:38:29.891942image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile38.160528
Maximum361.76374
Range361.76374
Interquartile range (IQR)0

Descriptive statistics

Standard deviation18.568437
Coefficient of variation (CV)3.1529332
Kurtosis65.635694
Mean5.8892579
Median Absolute Deviation (MAD)0
Skewness6.3829642
Sum72614.549
Variance344.78684
MonotonicityNot monotonic
2025-12-10T17:38:30.004657image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
09600
77.9%
53.9886
 
< 0.1%
42.293067523
 
< 0.1%
26.54552
 
< 0.1%
78.569598642
 
< 0.1%
87.90296062
 
< 0.1%
59.9882
 
< 0.1%
15.39562
 
< 0.1%
12.558857142
 
< 0.1%
42.4225312
 
< 0.1%
Other values (2694)2707
 
22.0%
ValueCountFrequency (%)
09600
77.9%
0.0380345421
 
< 0.1%
0.0670495461
 
< 0.1%
0.0935469491
 
< 0.1%
0.0986214031
 
< 0.1%
0.1206999141
 
< 0.1%
0.1296768931
 
< 0.1%
0.1318370131
 
< 0.1%
0.1392006231
 
< 0.1%
0.1506504981
 
< 0.1%
ValueCountFrequency (%)
361.76374191
< 0.1%
360.95338391
< 0.1%
287.95379281
< 0.1%
270.78469311
< 0.1%
261.49128571
< 0.1%
258.54987321
< 0.1%
255.56915791
< 0.1%
254.60715791
< 0.1%
246.75859021
< 0.1%
239.981
< 0.1%

SpecialDay
Real number (ℝ)

Zeros 

Distinct6
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.061427413
Minimum0
Maximum1
Zeros11079
Zeros (%)89.9%
Negative0
Negative (%)0.0%
Memory size96.5 KiB
2025-12-10T17:38:30.096043image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0.6
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.19891727
Coefficient of variation (CV)3.2382492
Kurtosis9.9136589
Mean0.061427413
Median Absolute Deviation (MAD)0
Skewness3.3026667
Sum757.4
Variance0.039568082
MonotonicityNot monotonic
2025-12-10T17:38:30.164295image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
011079
89.9%
0.6351
 
2.8%
0.8325
 
2.6%
0.4243
 
2.0%
0.2178
 
1.4%
1154
 
1.2%
ValueCountFrequency (%)
011079
89.9%
0.2178
 
1.4%
0.4243
 
2.0%
0.6351
 
2.8%
0.8325
 
2.6%
1154
 
1.2%
ValueCountFrequency (%)
1154
 
1.2%
0.8325
 
2.6%
0.6351
 
2.8%
0.4243
 
2.0%
0.2178
 
1.4%
011079
89.9%

Month
Categorical

Distinct10
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size96.5 KiB
May
3364 
Nov
2998 
Mar
1907 
Dec
1727 
Oct
549 
Other values (5)
1785 

Length

Max length4
Median length3
Mean length3.0233577
Min length3

Characters and Unicode

Total characters37278
Distinct characters22
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMay
2nd rowAug
3rd rowNov
4th rowNov
5th rowMay

Common Values

ValueCountFrequency (%)
May3364
27.3%
Nov2998
24.3%
Mar1907
15.5%
Dec1727
14.0%
Oct549
 
4.5%
Sep448
 
3.6%
Aug433
 
3.5%
Jul432
 
3.5%
June288
 
2.3%
Feb184
 
1.5%

Length

2025-12-10T17:38:30.260435image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-12-10T17:38:30.351228image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
may3364
27.3%
nov2998
24.3%
mar1907
15.5%
dec1727
14.0%
oct549
 
4.5%
sep448
 
3.6%
aug433
 
3.5%
jul432
 
3.5%
june288
 
2.3%
feb184
 
1.5%

Most occurring characters

ValueCountFrequency (%)
M5271
14.1%
a5271
14.1%
y3364
9.0%
N2998
8.0%
o2998
8.0%
v2998
8.0%
e2647
7.1%
c2276
 
6.1%
r1907
 
5.1%
D1727
 
4.6%
Other values (12)5821
15.6%

Most occurring categories

ValueCountFrequency (%)
(unknown)37278
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
M5271
14.1%
a5271
14.1%
y3364
9.0%
N2998
8.0%
o2998
8.0%
v2998
8.0%
e2647
7.1%
c2276
 
6.1%
r1907
 
5.1%
D1727
 
4.6%
Other values (12)5821
15.6%

Most occurring scripts

ValueCountFrequency (%)
(unknown)37278
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
M5271
14.1%
a5271
14.1%
y3364
9.0%
N2998
8.0%
o2998
8.0%
v2998
8.0%
e2647
7.1%
c2276
 
6.1%
r1907
 
5.1%
D1727
 
4.6%
Other values (12)5821
15.6%

Most occurring blocks

ValueCountFrequency (%)
(unknown)37278
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
M5271
14.1%
a5271
14.1%
y3364
9.0%
N2998
8.0%
o2998
8.0%
v2998
8.0%
e2647
7.1%
c2276
 
6.1%
r1907
 
5.1%
D1727
 
4.6%
Other values (12)5821
15.6%

OperatingSystems
Real number (ℝ)

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.1240065
Minimum1
Maximum8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size48.3 KiB
2025-12-10T17:38:30.448058image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q33
95-th percentile3
Maximum8
Range7
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.91132483
Coefficient of variation (CV)0.42905934
Kurtosis10.456843
Mean2.1240065
Median Absolute Deviation (MAD)0
Skewness2.066285
Sum26189
Variance0.83051294
MonotonicityNot monotonic
2025-12-10T17:38:30.519183image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
26601
53.5%
12585
 
21.0%
32555
 
20.7%
4478
 
3.9%
879
 
0.6%
619
 
0.2%
77
 
0.1%
56
 
< 0.1%
ValueCountFrequency (%)
12585
 
21.0%
26601
53.5%
32555
 
20.7%
4478
 
3.9%
56
 
< 0.1%
619
 
0.2%
77
 
0.1%
879
 
0.6%
ValueCountFrequency (%)
879
 
0.6%
77
 
0.1%
619
 
0.2%
56
 
< 0.1%
4478
 
3.9%
32555
 
20.7%
26601
53.5%
12585
 
21.0%

Browser
Real number (ℝ)

Distinct13
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.3570965
Minimum1
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size48.3 KiB
2025-12-10T17:38:30.593338image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q32
95-th percentile5
Maximum13
Range12
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.7172767
Coefficient of variation (CV)0.72855594
Kurtosis12.746733
Mean2.3570965
Median Absolute Deviation (MAD)0
Skewness3.2423496
Sum29063
Variance2.9490392
MonotonicityNot monotonic
2025-12-10T17:38:30.675857image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
27961
64.6%
12462
 
20.0%
4736
 
6.0%
5467
 
3.8%
6174
 
1.4%
10163
 
1.3%
8135
 
1.1%
3105
 
0.9%
1361
 
0.5%
749
 
0.4%
Other values (3)17
 
0.1%
ValueCountFrequency (%)
12462
 
20.0%
27961
64.6%
3105
 
0.9%
4736
 
6.0%
5467
 
3.8%
6174
 
1.4%
749
 
0.4%
8135
 
1.1%
91
 
< 0.1%
10163
 
1.3%
ValueCountFrequency (%)
1361
 
0.5%
1210
 
0.1%
116
 
< 0.1%
10163
 
1.3%
91
 
< 0.1%
8135
 
1.1%
749
 
0.4%
6174
 
1.4%
5467
3.8%
4736
6.0%

Region
Real number (ℝ)

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1473642
Minimum1
Maximum9
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size48.3 KiB
2025-12-10T17:38:30.741320image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median3
Q34
95-th percentile8
Maximum9
Range8
Interquartile range (IQR)3

Descriptive statistics

Standard deviation2.4015912
Coefficient of variation (CV)0.76304842
Kurtosis-0.1486803
Mean3.1473642
Median Absolute Deviation (MAD)2
Skewness0.98354916
Sum38807
Variance5.7676405
MonotonicityNot monotonic
2025-12-10T17:38:30.811904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
14780
38.8%
32403
19.5%
41182
 
9.6%
21136
 
9.2%
6805
 
6.5%
7761
 
6.2%
9511
 
4.1%
8434
 
3.5%
5318
 
2.6%
ValueCountFrequency (%)
14780
38.8%
21136
 
9.2%
32403
19.5%
41182
 
9.6%
5318
 
2.6%
6805
 
6.5%
7761
 
6.2%
8434
 
3.5%
9511
 
4.1%
ValueCountFrequency (%)
9511
 
4.1%
8434
 
3.5%
7761
 
6.2%
6805
 
6.5%
5318
 
2.6%
41182
 
9.6%
32403
19.5%
21136
 
9.2%
14780
38.8%

TrafficType
Real number (ℝ)

Distinct20
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.0695864
Minimum1
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size48.3 KiB
2025-12-10T17:38:30.888818image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median2
Q34
95-th percentile13
Maximum20
Range19
Interquartile range (IQR)2

Descriptive statistics

Standard deviation4.0251692
Coefficient of variation (CV)0.98908557
Kurtosis3.4797106
Mean4.0695864
Median Absolute Deviation (MAD)1
Skewness1.9629867
Sum50178
Variance16.201987
MonotonicityNot monotonic
2025-12-10T17:38:30.969313image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
23913
31.7%
12451
19.9%
32052
16.6%
41069
 
8.7%
13738
 
6.0%
10450
 
3.6%
6444
 
3.6%
8343
 
2.8%
5260
 
2.1%
11247
 
2.0%
Other values (10)363
 
2.9%
ValueCountFrequency (%)
12451
19.9%
23913
31.7%
32052
16.6%
41069
 
8.7%
5260
 
2.1%
6444
 
3.6%
740
 
0.3%
8343
 
2.8%
942
 
0.3%
10450
 
3.6%
ValueCountFrequency (%)
20198
 
1.6%
1917
 
0.1%
1810
 
0.1%
171
 
< 0.1%
163
 
< 0.1%
1538
 
0.3%
1413
 
0.1%
13738
6.0%
121
 
< 0.1%
11247
 
2.0%

VisitorType
Categorical

Imbalance 

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size96.5 KiB
Returning_Visitor
10551 
New_Visitor
1694 
Other
 
85

Length

Max length17
Median length17
Mean length16.092944
Min length5

Characters and Unicode

Total characters198426
Distinct characters16
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowReturning_Visitor
2nd rowReturning_Visitor
3rd rowReturning_Visitor
4th rowReturning_Visitor
5th rowNew_Visitor

Common Values

ValueCountFrequency (%)
Returning_Visitor10551
85.6%
New_Visitor1694
 
13.7%
Other85
 
0.7%

Length

2025-12-10T17:38:31.057508image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-12-10T17:38:31.113360image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
returning_visitor10551
85.6%
new_visitor1694
 
13.7%
other85
 
0.7%

Most occurring characters

ValueCountFrequency (%)
i35041
17.7%
t22881
11.5%
r22881
11.5%
n21102
10.6%
e12330
 
6.2%
s12245
 
6.2%
V12245
 
6.2%
_12245
 
6.2%
o12245
 
6.2%
g10551
 
5.3%
Other values (6)24660
12.4%

Most occurring categories

ValueCountFrequency (%)
(unknown)198426
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
i35041
17.7%
t22881
11.5%
r22881
11.5%
n21102
10.6%
e12330
 
6.2%
s12245
 
6.2%
V12245
 
6.2%
_12245
 
6.2%
o12245
 
6.2%
g10551
 
5.3%
Other values (6)24660
12.4%

Most occurring scripts

ValueCountFrequency (%)
(unknown)198426
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
i35041
17.7%
t22881
11.5%
r22881
11.5%
n21102
10.6%
e12330
 
6.2%
s12245
 
6.2%
V12245
 
6.2%
_12245
 
6.2%
o12245
 
6.2%
g10551
 
5.3%
Other values (6)24660
12.4%

Most occurring blocks

ValueCountFrequency (%)
(unknown)198426
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
i35041
17.7%
t22881
11.5%
r22881
11.5%
n21102
10.6%
e12330
 
6.2%
s12245
 
6.2%
V12245
 
6.2%
_12245
 
6.2%
o12245
 
6.2%
g10551
 
5.3%
Other values (6)24660
12.4%

Weekend
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
False
9462 
True
2868 
ValueCountFrequency (%)
False9462
76.7%
True2868
 
23.3%
2025-12-10T17:38:31.168229image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Revenue
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size12.2 KiB
False
10422 
True
1908 
ValueCountFrequency (%)
False10422
84.5%
True1908
 
15.5%
2025-12-10T17:38:31.209648image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Interactions

2025-12-10T17:38:25.866418image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:08.498961image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:09.741746image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:11.105637image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:12.564306image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:13.845927image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:15.163799image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:16.499486image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:17.818057image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:19.207848image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:20.562139image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:21.761191image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:23.131913image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:24.373151image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:25.959147image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:08.575050image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:09.830070image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:11.193791image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:12.647414image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:13.932179image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:15.257258image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:16.589510image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:17.906384image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:19.290040image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:20.642671image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:21.853030image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:23.211820image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:24.460047image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:26.053584image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:08.660058image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:09.923896image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:11.426407image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:12.733772image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:14.024132image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:15.346919image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:16.683543image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:18.005719image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:19.381289image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:20.729594image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:22.019606image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:23.295841image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:24.550907image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:26.137856image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:08.740158image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:10.008917image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:11.507504image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:12.815701image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:14.114851image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:15.432275image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:16.772715image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:18.105933image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:19.464091image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:20.807957image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:22.104712image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:23.377751image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:24.635946image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:26.230544image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:08.820161image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:10.148714image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:11.601983image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:12.898530image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:14.200352image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:15.517840image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:16.862490image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:18.196638image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:19.552697image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:20.900206image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:22.191236image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:23.457740image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:24.723658image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:26.322085image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:08.912193image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:10.254591image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:11.727185image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:12.996033image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:14.288784image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:15.609215image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:16.963414image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:18.302842image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:19.643226image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:20.988376image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:22.283074image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:23.543066image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:24.823595image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:26.463272image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:08.993906image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:10.346623image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:11.813748image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:13.139630image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:14.378575image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:15.695711image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:17.058496image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:18.438040image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:19.740608image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:21.075493image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:22.372071image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:23.632759image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:24.915931image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:26.598575image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:09.087882image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:10.442546image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:11.909448image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:13.233374image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:14.472073image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:15.799184image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:17.156726image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:18.532209image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:19.843790image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:21.167378image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:22.465904image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:23.724572image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:25.015482image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:26.727322image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:09.178755image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:10.539591image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:11.998382image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:13.321994image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:14.569469image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:15.893902image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:17.253476image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:18.635788image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:19.963229image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:21.259676image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:22.575774image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:23.871641image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:25.172827image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:26.859224image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:09.263487image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:10.641592image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:12.083816image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:13.410160image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:14.666291image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:15.987614image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:17.347711image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:18.729439image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:20.058837image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:21.343933image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:22.674469image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:23.955119image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:25.262261image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:27.038596image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:09.341533image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:10.730165image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:12.197321image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:13.494411image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:14.800556image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:16.074082image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:17.436647image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:18.824290image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:20.148580image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:21.428877image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:22.765374image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:24.032888image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:25.354903image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:27.164460image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:09.430070image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:10.822067image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:12.287203image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:13.590265image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:14.895313image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:16.161298image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:17.537108image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:18.923727image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:20.289289image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:21.510590image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:22.852418image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:24.115643image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:25.603595image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:27.278438image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:09.509997image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:10.910619image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:12.372846image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:13.674734image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:14.978070image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:16.254040image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:17.625662image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:19.009931image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:20.378905image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:21.593760image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:22.938614image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:24.193955image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:25.688219image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:27.402934image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:09.597140image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:11.007908image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:12.475796image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:13.761987image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:15.073038image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:16.371083image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:17.718512image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:19.107114image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:20.467704image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:21.678515image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:23.025861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:24.282984image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-12-10T17:38:25.777583image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-12-10T17:38:31.275754image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
AdministrativeAdministrative_DurationBounceRatesBrowserExitRatesInformationalInformational_DurationMonthOperatingSystemsPageValuesProductRelatedProductRelated_DurationRegionRevenueSpecialDayTrafficTypeVisitorTypeWeekend
Administrative1.0000.941-0.155-0.012-0.4340.3690.3630.051-0.0050.3280.4600.4220.0090.131-0.125-0.0120.0860.028
Administrative_Duration0.9411.000-0.164-0.023-0.4380.3570.3520.020-0.0070.3170.4300.4140.0190.064-0.132-0.0150.0070.000
BounceRates-0.155-0.1641.000-0.0470.6020.006-0.0020.0550.053-0.124-0.052-0.080-0.0180.1700.1350.0160.1230.050
Browser-0.012-0.023-0.0471.000-0.016-0.020-0.0130.0590.3750.0260.0440.0460.0550.0380.0210.0000.4720.059
ExitRates-0.434-0.4380.602-0.0161.000-0.186-0.2000.0580.022-0.308-0.519-0.477-0.0040.2450.1510.0220.1840.065
Informational0.3690.3570.006-0.020-0.1861.0000.9510.0170.0000.2190.3690.368-0.0230.078-0.054-0.0290.0280.011
Informational_Duration0.3630.352-0.002-0.013-0.2000.9511.0000.0090.0030.2240.3610.363-0.0150.068-0.054-0.0260.0080.000
Month0.0510.0200.0550.0590.0580.0170.0091.0000.0570.0190.0690.0470.0370.1750.2360.1600.1380.058
OperatingSystems-0.005-0.0070.0530.3750.0220.0000.0030.0571.000-0.0120.0210.0230.0270.0740.0230.0800.4650.118
PageValues0.3280.317-0.1240.026-0.3080.2190.2240.019-0.0121.0000.3420.3600.0010.413-0.070-0.0180.1100.031
ProductRelated0.4600.430-0.0520.044-0.5190.3690.3610.0690.0210.3421.0000.883-0.0210.127-0.022-0.0700.0790.000
ProductRelated_Duration0.4220.414-0.0800.046-0.4770.3680.3630.0470.0230.3600.8831.000-0.0100.072-0.050-0.0730.0350.004
Region0.0090.019-0.0180.055-0.004-0.023-0.0150.0370.0270.001-0.021-0.0101.0000.010-0.015-0.0040.1800.017
Revenue0.1310.0640.1700.0380.2450.0780.0680.1750.0740.4130.1270.0720.0101.0000.0860.1210.1040.028
SpecialDay-0.125-0.1320.1350.0210.151-0.054-0.0540.2360.023-0.070-0.022-0.050-0.0150.0861.0000.1100.0640.259
TrafficType-0.012-0.0150.0160.0000.022-0.029-0.0260.1600.080-0.018-0.070-0.073-0.0040.1210.1101.0000.3160.092
VisitorType0.0860.0070.1230.4720.1840.0280.0080.1380.4650.1100.0790.0350.1800.1040.0640.3161.0000.054
Weekend0.0280.0000.0500.0590.0650.0110.0000.0580.1180.0310.0000.0040.0170.0280.2590.0920.0541.000

Missing values

2025-12-10T17:38:27.573407image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-12-10T17:38:27.749439image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

AdministrativeAdministrative_DurationInformationalInformational_DurationProductRelatedProductRelated_DurationBounceRatesExitRatesPageValuesSpecialDayMonthOperatingSystemsBrowserRegionTrafficTypeVisitorTypeWeekendRevenue
000.0000.022370.3333330.0181820.0545450.000000.6May22413Returning_VisitorFalseFalse
112381.50122.21547835.8746290.0125500.0225880.000000.0Aug3212Returning_VisitorTrueFalse
2544.75351.51073074.8527780.0154550.0262400.000000.0Nov2231Returning_VisitorTrueFalse
3112.0000.011213.0000000.0500000.0666670.000000.0Nov22413Returning_VisitorTrueFalse
400.0000.010.0000000.2000000.2000000.000000.0May1133New_VisitorFalseFalse
5118.00116.033504.0000000.0060610.0333330.000000.0May2414Returning_VisitorFalseFalse
6151.4000.07562.3000000.0000000.00000036.657350.0Jul1162New_VisitorTrueTrue
7246.4000.08349.0000000.0200000.0800000.000000.0Aug4111Returning_VisitorFalseFalse
8454.4000.0682889.9461540.0028990.0087890.000000.0June4141Returning_VisitorFalseFalse
93335.50115.0496.0000000.0000000.0250000.000000.0Nov11815Returning_VisitorFalseFalse
AdministrativeAdministrative_DurationInformationalInformational_DurationProductRelatedProductRelated_DurationBounceRatesExitRatesPageValuesSpecialDayMonthOperatingSystemsBrowserRegionTrafficTypeVisitorTypeWeekendRevenue
1232000.00000000.000201395.2583330.0000000.0111110.0000000.0Mar1119New_VisitorTrueFalse
12321146.50000000.000402338.9500000.0170730.0303259.4729140.0Nov1113Returning_VisitorFalseTrue
12322336.00000000.000329.5000000.0000000.0400000.0000000.0Nov21032OtherFalseFalse
1232313408.60000000.00021589.4214290.0044440.01481518.0985720.0Aug2282Returning_VisitorFalseTrue
12324133.50000000.00033880.6333330.0000000.0341180.0000000.0Dec2243Returning_VisitorFalseFalse
1232500.00000000.000255.0000000.0000000.0500000.0000000.4May32113Returning_VisitorFalseFalse
1232600.00000000.00011251.2916670.0000000.0111110.0000000.0Nov32211Returning_VisitorTrueFalse
1232700.00000000.00017141.5000000.0823530.1117650.0000000.6May2216Returning_VisitorFalseFalse
123284302.50000000.00015257.1666670.0500000.0487500.0000000.0Dec3273Returning_VisitorFalseFalse
1232912275.5166672288.375601276.5940480.0000000.0095245.4524330.0Nov4112Returning_VisitorFalseTrue

Duplicate rows

Most frequently occurring

AdministrativeAdministrative_DurationInformationalInformational_DurationProductRelatedProductRelated_DurationBounceRatesExitRatesPageValuesSpecialDayMonthOperatingSystemsBrowserRegionTrafficTypeVisitorTypeWeekendRevenue# duplicates
2600.000.010.00.20.20.00.0Mar2211Returning_VisitorFalseFalse14
3600.000.010.00.20.20.00.0Mar3231Returning_VisitorFalseFalse7
4400.000.010.00.20.20.00.0May2213Returning_VisitorFalseFalse7
3800.000.010.00.20.20.00.0May1113Returning_VisitorFalseFalse6
1300.000.010.00.20.20.00.0Dec813920OtherFalseFalse5
3400.000.010.00.20.20.00.0Mar3211Returning_VisitorFalseFalse4
4100.000.010.00.20.20.00.0May1143Returning_VisitorFalseFalse4
6000.000.010.00.20.20.00.0Nov2211Returning_VisitorFalseFalse4
000.000.010.00.20.20.00.0Dec1111Returning_VisitorTrueFalse3
300.000.010.00.20.20.00.0Dec1141Returning_VisitorTrueFalse3